Transformers
PyTorch
Safetensors
t5
text2text-generation
Trinidadian Creole
Caribbean dialect
text-generation-inference
Instructions to use KES/ENG-TEC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KES/ENG-TEC with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("KES/ENG-TEC") model = AutoModelForSeq2SeqLM.from_pretrained("KES/ENG-TEC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 944cd8a9c2815f7bf77beccb5eee32d2cb579b85c9a4b7d11d3917a8d7685deb
- Size of remote file:
- 892 MB
- SHA256:
- 9f8504671400e57bc3becce56bb39d8332b6f6c0bab60f2ede0fb690519c5249
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.